coef.cv.glmgraph {glmgraph} | R Documentation |
Retrieve coefficients from a fitted "cv.glmgraph" object based on the chosen regularization parameters from cross validation.
## S3 method for class 'cv.glmgraph' coef(object,s,...)
object |
Fitted |
s |
Either |
... |
Other parameters to |
Li Chen <li.chen@emory.edu> , Jun Chen <chen.jun2@mayo.edu>
Li Chen. Han Liu. Hongzhe Li. Jun Chen. (2015) glmgraph: Graph-constrained Regularization for Sparse Generalized Linear Models.(Working paper)
predict.cv.glmgraph
,cv.glmgraph
set.seed(1234) library(glmgraph) n <- 100 p1 <- 10 p2 <- 90 p <- p1+p2 X <- matrix(rnorm(n*p), n,p) magnitude <- 1 ## construct laplacian matrix from adjacency matrix A <- matrix(rep(0,p*p),p,p) A[1:p1,1:p1] <- 1 A[(p1+1):p,(p1+1):p] <- 1 diag(A) <- 0 diagL <- apply(A,1,sum) L <- -A diag(L) <- diagL btrue <- c(rep(magnitude,p1),rep(0,p2)) intercept <- 0 eta <- intercept+X%*%btrue ### gaussian Y <- eta+rnorm(n) cv.obj <- cv.glmgraph(X,Y,L) beta.min <- coef(cv.obj)